Theoretical Courses

Cognitive Neuroscience - Intelligence

Lecture 1. Introduction to intelligence

  1. Early definitions of intelligence: single factor vs multiple factors
  2. Construct validity and construct reliability
  3. Scientific definitions of intelligence (Francis Galton, James McKeen Cattell, Alfred Binet, Henry Goddard, Lewis Terman, Robert Yerkes)
  4. The origin of the Intelligence Quotient (IQ) tests
  5. The early tests: Binet and Simon’s scales, Stanford-Binet scale, the Alpha and Beta tests


How the Brain Tells Time

This course will offer an overview of the state of the art of the neuroscience of time, from theoretical models to empirical data. Particular emphasis will be given to the perception of time. 

Introduction to Systems and Computational Neuroscience: Evolution of Neural Computation

The course delineates the evolution of the vertebrate nervous systems, with a particular focus on mammals and among them on the human lineage.

Introduction to Systems and Computational Neuroscience: Tactile Perception

This course focuses on the basic principles of organization of the sensory pathways and their target regions of cerebral cortex.

Introduction to Systems and Computational Neuroscience: Visual Perception

The course focuses on the structure and functions of the mammalian visual systems, with a special emphasis on shape processing and object recognition.

Language, Reading and the Brain

This course offers an introduction to how the brain deals with language and reading by focusing on the relationship between form and meaning -- is it arbitrary or not? Is it all about one-to-one associations, or are there probabilistic, high-dimensional patterns that the brain captures?

Learning, Inference, and Prediction in the Brain

This course is an introduction to the brain as a predictive organ. The brain learns about its environment and infers the state of that environment in order to predict it, which will help ensure its own survival.

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